Feedback mechanism refers to carrying a notion of output to the previous states, allowing the model to have a self-correcting procedure. It is worth noting that the feedback mechanism is different from recursive learning since in the feedback mechanism the model parameters are keeping self-correcting and do not share. Recently, feedback mechanism has been widely used in many
computer vision tasks [1]}, [2]}, which is also beneficial for the SR images reconstruction. Specifically, the feedback mechanism allows the network to carry high-level information back to previous layers and refine low-level information, thus fully guide the LR image to recover high-quality SR images.
